Pharmacoinformatics Protocol to Predict the Modulators of ABL & SRC for the Chemotherapeutic Treatment of Helicobacter Pylori Induced Gastric Cancer

Abstract

Gastric cancer is an aggressive universal disease that impose a daunting impact on global health burden. Helicobacter Pylori is mainly considered the robust risk factor in the progression of gastric cancer. The oncoprotein of Helicobacter Pylori, CagA is primarily involved in the carcinogenic process of gastric cancer along with some other environmental, habitual, and genetic risk factors. Two important human proteins c-src and c-abl play a crucial role in signal cascade of gastric cancer by activating from Helicobacter Pylori and then activating the CagA. Thus, the inhibition of c-src and c-abl proteins might be a promising strategy towards the control of gastric cancer. Plenty of the inhibitors designed against kinase proteins but none of the type I I I inhibitors against c-src and c-abl could be able to reach the market. Computational approach to probe the 3D structural features of c-src and c-abl modulators might be a worthwhile strategy towards finding of potent possible modulators against gastric cancer. To achieve this goal both ligand and structure-based approach were used in this project. In structure base study homology model of c-src was constructed as its recent crystal structure was not available. In addition to this, the binding hypothesis of c-src and c-abl was predicted by molecular docking. Molecular docking of c-src revealed that ASN368, GLU316, PHE382, THR315, MET318 and ASN322 are important residues in the vicinity of binding pocket to prob the hydrogen bond interaction with ligands. Molecular docking of c-abl revealed that GLU155, HIS127, GLU48, LEU51, THR44 ALA49 and LYS170 are important residues in the vicinity of binding pocket to prob the hydrogen bond interaction with ligands. In ligand base study we classify the ligands in different classes based on the presence of common scaffold. We develop the pharmacophore model based on the results of docking study for both c-src and c-abl by selecting the template using active analogue approach. The predictive model of c-src indicates the specificity of model 69% and sensitivity 70 % while the model of c-abl indicates 95% specificity and 85% sensitivity. The presence one aromatic feature at 6.28 Å from the other aromatic feature might contribute to selectivity of c-src. Thus, it seems that binding cavity of c-src is more hydrophobic / aromatic as compared to c-abl that contain one large hydrogen bond accepter feature. Through virtual screening of natural database, we identify some plant’s extracts that might be an effective against gastric cancer xvi In a nutshell, we were able to establish a binding hypothesis of c-abl and c-src and to probe important 3D interaction features of inhibitors of c-abl and c-src and identified some plant’s extracts that might act as future lead compounds against gastric cancer.